Management methods, management systems, and electronic medical record systems

Abstract

This management method comprises: a determination step of a management system using an estimated time or a record-based required time for an analysis institution to analyze a gene of a specimen of a patient, an estimated time or a record-based required time for a creating institution to create from a gene analysis result a recipe for an administered substance for the patient, and / or an estimated time or a record-based required time for a manufacturing institution to manufacture the administered substance from the recipe, to determine a predicted date of delivery or a predicted time required for delivering the administered substance to a hospital; and a transmitting step for transmitting information for displaying the predicted date of delivery or the predicted time required to a terminal.

Description

Technical Field

[0001] The present invention relates to a management method, a management system, and an electronic medical record system.

Background Art

[0002] In conventional cancer treatment, treatments and drugs have been selected according to the type of cancer such as lung cancer, colorectal cancer, and breast cancer. However, since the 2000s, the elucidation of molecules (proteins) that cause cancer and gene mutations that are the basis thereof has advanced, and "molecularly targeted drugs" that act on such molecules and genes can be used for treatment. Further developed from molecularly targeted drugs, treatment methods targeting the molecular and gene mutations of individual patients have also been developed. Here, performing treatment suitable for each person according to the characteristics of cancer such as gene mutations as well as the type of cancer is called "personalized treatment". Conventionally, "personalized treatment" based on cancer gene information has been mainly performed based on "cancer gene testing" that examines a small number of genes and "cancer gene panel testing" that examines a large number of genes simultaneously.

[0003] In recent years, treatment using cancer immunotherapy (hereinafter referred to as cancer vaccine treatment), in which cancer cells are attacked and eliminated by the action of the immune system that humans originally have, has advanced. "Peptide vaccine" is known as one of cancer vaccine treatments. The peptide vaccine contains an antigen that is a mark of cancer. When the peptide containing this antigen is directly injected into the body, the immune function that humans originally have detects the abnormality and attacks the antigen that is a mark of cancer to kill cancer cells.

[0004] In recent years, with the advent of a technology that allows for comprehensive and easy identification of genetic mutations in each patient's cancer, the importance of "peptides" newly generated by these genetic mutations has been highlighted in cancer immunotherapy. These peptides are mutated peptides called "neoantigens." When these peptides appear on the surface of cancer cells via human leukocyte antigens (HLA), it has become clear that cytotoxic T lymphocytes (CTLs) recognize them as enemies and can kill cancer cells because they are peptides not found on the surface of normal cells. Currently, clinical trials are being conducted in Europe and the United States to determine whether personalized cancer vaccine therapy using "neoantigens" is effective as a treatment for cancer and a method for preventing recurrence. Furthermore, Patent Document 1 discloses a method for identifying immunogenic polypeptide fragments in specific human subjects and a method for preparing personalized pharmaceutical compositions containing said polypeptide fragments. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Special Publication No. 2020-510698 [Overview of the Initiative] [Problems that the invention aims to solve]

[0006] Because the types and numbers of mutated peptides called "neoantigens" differ from patient to patient, it is necessary to produce peptide vaccines individually for each patient, based on the gene mutations in the patient's cancer tissue. In the case of personalized medicine (for example, personalized cancer vaccine therapy), there are three processes: a gene analysis laboratory (for example, a sequencing vendor) analyzes the genes of the patient's sample; a recipe creation laboratory creates a recipe for the drug (for example, a vaccine) from the gene analysis results; and a vaccine manufacturing laboratory manufactures the drug (for example, a vaccine) from this recipe.

[0007] Since vaccine production involves multiple processes, and it is expected that some or most of these processes will be outsourced to external vendors, it is highly likely that production will be on a build-to-order basis. Therefore, there is a problem in that it is difficult to determine the delivery date of the administered substance (e.g., vaccine) to be given to patients. Furthermore, not only cancer vaccines, but also autoimmune diseases may have similar treatment possibilities, and the same problems exist in personalized medicine for autoimmune diseases.

[0008] This invention has been made in view of the above problems, and aims to provide a management method, a management system, and an electronic medical record system that enable tracking of delivery dates for individualized medicine doses. [Means for solving the problem]

[0009] A management method according to a first aspect of the present invention includes a determination step in which the management system determines a predicted delivery date or predicted time required for the administration to be delivered to the hospital, using the estimated time or actual time required for the analysis institution to analyze the genes of the patient's sample, the estimated time or actual time required for the preparation institution to create a recipe for the administration to the patient from the gene analysis results, and / or the estimated time or actual time required for the manufacturing institution to manufacture the administration from the recipe; and a transmission step in which information for displaying the predicted delivery date or predicted time required is transmitted to a terminal.

[0010] A management method according to a second aspect of the present invention is a management method according to a first aspect, wherein there are multiple candidates for the analysis institution and / or the preparation institution and / or the manufacturing institution, and in the decision step, the predicted delivery date or predicted time required for the administration body to be delivered to the hospital is determined according to the analysis institution and / or the preparation institution and / or the manufacturing institution to which the order is placed.

[0011] A third aspect of the present invention is a management method according to the first or second aspect, comprising the step of the management system sending back information to the terminal for displaying the progress status of the administered substance when a request for the progress status of the administered substance is received from the terminal.

[0012] A management method according to a fourth aspect of the present invention is a management method according to a third aspect, wherein viewing rights are assigned to each institution and stored in a storage device, and in the step of replying, the step of replying the progress status is to the extent permitted by the viewing rights assigned to the institution to which the terminal that requested the progress status belongs.

[0013] A management method according to a fifth aspect of the present invention is a management method according to any of the first to fourth aspects, which includes the step of notifying the physician terminal logged into the service provided by the patient's attending physician or the patient's attending physician if the delivery is delayed from the predicted delivery date or the predicted required time.

[0014] A management method according to a sixth aspect of the present invention is a management method according to any of the first to fifth aspects, comprising the step of enabling the setting of an administration schedule for the patient when the confidence level of the delivery date exceeds a standard.

[0015] A management method according to a seventh aspect of the present invention is a management method according to any of the first to sixth aspects, comprising the steps of: when gene sequence data is received from the analysis institution, the management system transmits the gene sequence data to the system of the production institution; and when a recipe is received from the production institution, the management system transmits the recipe to the system of the manufacturing institution.

[0016] A management method according to an eighth aspect of the present invention is a management method according to any of the first to seven aspects, wherein when the management system receives quality information regarding a sample, quality information regarding gene sequencing, quality information regarding a recipe, and / or quality information regarding a vaccine from a hospital system, an analysis laboratory system, a preparation laboratory system, and / or a manufacturing laboratory system, the management system has the step of storing the received information in a storage device.

[0017] A control method according to a ninth aspect of the present invention is a control method according to an eighth aspect, wherein the administered substance is a vaccine, and the recipe is peptide sequence data of a neoantigen, protein data, or aggregate data of administered compounds.

[0018] A management method according to a tenth aspect of the present invention is a management method according to any of the first to nine aspects, comprising the step of writing the update history and / or update data of the storage device to a blockchain.

[0019] An eleventh aspect of the present invention is a management method according to any of the first to ten aspects, comprising the step of determining an estimated time for analyzing the gene according to the number of gene fragments obtained from the sample and / or the base amount of the gene to be read.

[0020] A management method according to a twelfth aspect of the present invention is a management method according to any of the first to eleven aspects, comprising the step of determining an estimated time for creating the recipe according to the amount of sequence data obtained as a result of gene analysis.

[0021] A management method according to a thirteenth aspect of the present invention is a management method according to any of the first to eleven aspects, comprising the step of determining the estimated time to prepare the recipe according to the number of gene mutations.

[0022] A management method according to a 14th aspect of the present invention is a management method according to any of the 1 to 11 aspects, comprising the step of determining the estimated time to prepare the recipe according to the name of the organ from which the specimen was obtained.

[0023] The management method according to the 15th aspect of the present invention is the management method according to any one of the 1st to 11th aspects, and is configured to input at least one of the number of gene fragments and / or the base amount of genes to be read, the sequence data amount, and the number of gene mutations, and output a predicted delivery date using the learning data for training a machine learning model. By inputting at least one of the number of gene fragments and / or the base amount of genes to be read, the sequence data amount, and the number of gene mutations into the machine learning model, the estimated time for creating the recipe is determined.

[0024] The management method according to the 16th aspect of the present invention is the management method according to any one of the 1st to 15th aspects, and further includes an access control step of restricting information accessible for each institution.

[0025] The management system according to the 17th aspect of the present invention includes a delivery date management means for determining a predicted delivery date or predicted required time for the dosage form to be delivered to the hospital using the estimated time or actual required time for an analysis institution to analyze the genes of a patient's sample, the estimated time or actual required time for a creation institution to create a recipe for the dosage form for the patient from the gene analysis results, and the estimated time or actual required time for a manufacturing institution to manufacture the dosage form from the recipe, and a communication control means for transmitting information for displaying the predicted delivery date or predicted required time to a terminal.

[0026] The electronic medical record system according to the 18th aspect of the present invention includes the management system according to the 17th aspect of the present invention.

Advantages of the Invention

[0027] According to one aspect of the present invention, since information for displaying the predicted delivery date or predicted required time of the dosage form for personalized medicine is displayed on the terminal, the delivery date of the dosage form for personalized medicine can be grasped.

Brief Description of the Drawings

[0028] [Figure 1] It is a schematic block diagram of the information processing system according to the present embodiment. [Figure 2]This is a schematic block diagram of the management system according to this embodiment. [Figure 3] This diagram shows the schematic configuration of the databases for each system in this embodiment. [Figure 4] This is an example of a sequence diagram according to this embodiment. [Figure 5] This is an example of a vaccine ordering screen displayed on a hospital terminal. [Figure 6] This is an example of a progress management screen displayed on a hospital terminal. [Figure 7] This is an example of a progress management screen displayed on the analyst's terminal, creator's terminal, or manufacturer's terminal. [Figure 8] This is an example of a list of access restrictions for the data being accessed. [Figure 9] This is an example of a search results screen displayed on a hospital terminal. [Figure 10] This diagram shows the schematic configuration of the databases for each system in the modified example 1. [Figure 11] This is an example of a sequence diagram relating to Modification 1. [Figure 12] This diagram shows the schematic configuration of the databases for each system in the modified example 2. [Figure 13] This is an example of a sequence diagram relating to Modification 2. [Figure 14] This is a schematic block diagram of an information processing system according to a modified example of this embodiment. [Modes for carrying out the invention]

[0029] The following descriptions of each embodiment will be made with reference to the drawings. However, unnecessarily detailed explanations may be omitted. For example, detailed explanations of already well-known matters and redundant explanations of substantially identical configurations may be omitted. This is to avoid the following explanation becoming unnecessarily verbose and to facilitate understanding for those skilled in the art.

[0030] <Problems of this embodiment> In the distribution of conventional pharmaceuticals, there is no need to link patient information due to mass production. In the case of cancer gene panel testing, patient data is confined to the hospital or genome sequencing company, and treatment selection (i.e., determination of administered drugs) is carried out based on the cancer gene panel test report and selected from existing drugs. Therefore, there was no need to link patient identification information (e.g., patient ID) or genomic data with drug identification information (e.g., drug ID).

[0031] Car-T does not require the analysis of patient genetic data, and in principle, the process can be managed only between the factory and the hospital. Since there are no genetic analysis institutions (e.g., sequencing vendors) or recipe development institutions, collaboration with them is not considered. In the case of personalized cancer vaccine therapy, the vaccine crosses multiple organizations and / or systems, so management is necessary, and process control and information sharing are important. However, in the Car-T supply chain, the process control and information sharing are limited to the physical transportation of samples and some associated data, resulting in insufficient process control and information sharing.

[0032] (1) Thus, since there has been no need to manage patients, patient genomes, and vaccines administered to patients in a linked manner in the past, there is a further challenge in that a method for appropriate management is desired. In response to this challenge, this embodiment provides a method for managing patients, patient genomes, and vaccines administered to patients. (2) Furthermore, unlike existing medical practices, it involves multiple organizations and / or systems, which presents an additional challenge: the need to manage information for each process (e.g., quality information, success / failure of each process, etc.). To address this challenge, the management system of this embodiment provides a pipeline management function that manages information for each process (e.g., quality information, success / failure of each process, etc.). (3) As supply chains may span multiple countries, there is a further challenge in that each country needs to properly manage personal information. To address this challenge, in this embodiment, access restrictions are set for each institution (system).

[0033] The recipe may be, for example, peptide sequence data of a neoantigen, protein data, or a set of administered compounds. In this embodiment, the administered substance will be a vaccine as an example, and the recipe will be the peptide sequence data of a neoantigen.

[0034] Figure 1 is a schematic block diagram of an information processing system according to the first embodiment. As shown in Figure 1, the information processing system S comprises hospital systems 1-1, ..., 1-N (where N is a natural number), a gene analysis laboratory system 2, a recipe creation laboratory system 3, a vaccine manufacturing laboratory system 4, and a management system 5 connected to these systems via a communication network CN. Each system is equipped with a storage device, and a database is constructed in the storage device as an example. Hospital systems 1-1, ..., 1-N are collectively referred to as hospital system 1.

[0035] Here, hospital system 1 is a computer system managed by the hospital and consists of one or more computers. Gene analysis institution system 2 is a computer system managed by a gene analysis institution (also simply called an analysis institution) and consists of one or more computers. A gene analysis institution is, for example, a sequencing vendor. Recipe creation institution system 3 is a computer system managed by a recipe creation institution (also simply called a creation institution) and consists of one or more computers. A recipe creation institution is, for example, a PCV (Personalized Cancer Vaccine) prediction vendor. Vaccine manufacturing institution system 4 is a computer system managed by a vaccine manufacturing institution (also simply called a manufacturing institution) and consists of one or more computers. A vaccine manufacturing institution is, for example, a vaccine manufacturing vendor.

[0036] Hospital system 1-i (where i is an integer from 1 to N) is connected to hospital terminal 11-i in a communication-enabled manner. Hospital terminal 11-i is installed in the hospital and is operated by medical personnel such as doctors and nurses. Hereinafter, hospital terminals 11-1, ..., 11-N will be collectively referred to as hospital terminal 11. Gene analysis facility system 2 is connected to analyzer terminal 21 in a communication-enabled manner. Recipe creation facility system 3 is connected to creator terminal 31 in a communication-enabled manner. Vaccine manufacturing facility system 4 is connected to manufacturer terminal 41 in a communication-enabled manner. Hereafter, the term "terminal" may refer collectively to the hospital terminal 11, the analyst terminal 21, the creator terminal 31, and the manufacturer terminal 41. Note that, as an example, this explanation describes a case where there is only one gene analysis system 2, one recipe creation system 3, and one vaccine manufacturing system 4. However, like the hospital system 1, there may be multiple gene analysis system 2, one recipe creation system 3, and one vaccine manufacturing system 4.

[0037] Management system 5 is a system managed by the administrator, and it notifies terminals (for example, hospital terminal 11, analyst terminal 21, creator terminal 31, manufacturer terminal 41) of the completion or progress of each process.

[0038] Figure 2 is a schematic block diagram of the management system according to this embodiment. As shown in Figure 2, the management system 5 includes, for example, an input interface 51, a communication module 52, storage 53, memory 54, an output interface 55, and a processor 56.

[0039] The input interface 51 receives input from the administrator of the management system 5 and outputs an input signal corresponding to the received input to the processor 56. The communication module 52 is connected to the communication network CN and communicates with the hospital terminal 11, the analyst terminal 21, the creator terminal 31, and the manufacturer terminal 41. This communication may be wired or wireless, but this explanation will assume it is wired.

[0040] Storage 53 is an example of a storage device, and stores programs and various data for the processor 56 to read and execute. In this embodiment, a database is built on storage 53 as an example. Memory 54 temporarily holds data and programs. Memory 54 is volatile memory, such as RAM (Random Access Memory). The output interface 55 can be connected to an external device and can output signals to that external device.

[0041] The processor 56 loads a program into memory (not shown) and executes a series of instructions contained in the program, thereby functioning as a delivery date management means 561, a communication control means 562, an ID management means 563, a pipeline management means 564, a genome information management means 565, a quality information management means 566, an access control means 567, and a blockchain processing means 568.

[0042] The delivery date management means 561 determines the predicted delivery date or predicted time required for the administration to be delivered to the hospital, using the estimated time or actual time required for the analysis institution to analyze the genes of the patient's sample, the estimated time or actual time required for the preparation institution to create a recipe for the administration (e.g., vaccine) from the gene analysis results, and / or the estimated time or actual time required for the manufacturing institution to manufacture the administration from the recipe.

[0043] The communication control means 562 transmits information for displaying the predicted delivery date or predicted required time to a terminal (for example, a hospital terminal 11, an analyst terminal 21, a creator terminal 31, or a manufacturer terminal 41). As a result, information for displaying the predicted delivery date or predicted required time of the personalized medicine agent (for example, a vaccine) is displayed on the terminal, so that the delivery date of the personalized medicine agent can be determined.

[0044] The ID management means 563 manages hospital IDs, which are examples of hospital identification information for identifying hospitals; patient IDs, which are examples of patient identification information for identifying patients; specimen IDs, which are examples of specimen identification information for identifying specimens; common IDs for common management; recipe IDs, which are examples of recipe identification information for identifying recipes; and vaccine IDs, which are examples of vaccine identification information for identifying vaccines. For example, by having the ID management means 563 store patient, genome information, and vaccine information in association with common IDs, centralized coordination between multiple systems becomes possible.

[0045] The pipeline management means 564 manages progress information (e.g., success / failure at each stage) of each process, including gene analysis, recipe creation, and vaccine manufacturing. For example, the pipeline management means 564 acquires the success / failure at each stage of vaccine manufacturing in real time and notifies the terminal of the success / failure at each stage in response to a request from the terminal. This allows administrators, doctors, and personnel at each institution to share the success / failure at each stage of vaccine manufacturing in real time.

[0046] For example, the pipeline management means 564 automatically acquires error occurrences from the hospital system 1, the gene analysis laboratory system 2, the recipe creation laboratory system 3, and the vaccine manufacturing laboratory system 4. This allows for quick detection of process abnormalities. The pipeline management means 564 also notifies the systems of subsequent processes and the hospital system of the error when it occurs. Furthermore, the pipeline management means 564 can shorten the recovery time in the event of an abnormality by notifying the systems of subsequent processes to stop the subsequent processing.

[0047] The genome information management device 565 manages the patient's genome information.

[0048] The quality information management means 566 manages data related to the quality of vaccine manufacturing. For example, the quality information management means 566 notifies the hospital terminal 11 of this data in response to a request from the hospital terminal 11. This allows the physician to refer to this data and use it to make decisions regarding vaccine administration.

[0049] For example, when the quality information management means 566 receives quality information regarding specimens, quality information regarding gene sequencing, quality information regarding recipes, and / or quality information regarding vaccines from a hospital system, an analysis laboratory system, a production laboratory system, and / or a manufacturing laboratory system, it stores the received information in the storage 53.

[0050] The genome information management means 565 and the quality information management means 566 enable the detection of tampering by keeping a history of database access and deletion.

[0051] The access control means 567 restricts the information that can be accessed for each institution. The access control means 567 may also determine the country from which the access originates and restrict access to patient information by determining access rights (institution, position, name, etc.) using certificates.

[0052] The blockchain processing means 568 manages the update history and / or update data of the storage 53 by writing it to the blockchain. This update history includes, for example, the history of viewing and deleting data in the storage 53 database. This makes it difficult to tamper with data during the process. Furthermore, this updated data includes, for example, data related to the process of the embodiment (e.g., various IDs, vaccine manufacturing progress information, patient genome information, and data related to the quality of vaccine manufacturing). This allows data to be restored from the blockchain even if the data in storage 53 is corrupted.

[0053] Furthermore, the blockchain processing means 568 may store only the update history on the blockchain. This ensures the confidentiality of the update data, as the update data itself is not stored on the blockchain.

[0054] In this embodiment, when the management system 5 receives a sample ID from the hospital system 1, it issues a common ID. Only the management system 5 manages the data using the common ID, while the hospital system 1 and the gene analysis laboratory system 2 manage the data using the sample ID, the recipe creation laboratory system 3 manages the data using the recipe ID, and the vaccine manufacturing laboratory system 4 manages the data using the vaccine ID.

[0055] Figure 3 is a diagram illustrating the schematic configuration of the databases for each system in this embodiment. As shown in Figure 3, the management system table T5 stores records of sets of information, including a hospital ID to identify the hospital, a patient ID to identify the patient, a specimen ID to identify the specimen, a common ID for managing the data, a sequence file name which is the name of the sequence file containing the gene sequence sequenced from the patient's specimen, a recipe ID to identify the vaccine recipe, a recipe file name which is the name of the recipe file containing the vaccine recipe, and a vaccine ID to identify the vaccine. Here, for example, the sequence file is stored in a directory predetermined for sequence files. Similarly, for example, the recipe file is stored in a directory predetermined for recipe files.

[0056] Here, sample IDs are assigned to both the patient's normal tissue or blood and the patient's cancerous tissue. As an example, the sample ID assigned to the patient's normal tissue or blood differs from the sample ID assigned to the patient's cancerous tissue only in its last digit.

[0057] The sequence files include files containing sequences of normal tissue DNA (also called normal DNA), files containing sequences of cancerous tissue DNA (also called cancer DNA), and files containing sequences of cancerous tissue RNA (also called cancer RNA). The file names of each sequence are stored in table T5, and each sequence file is stored in storage 53.

[0058] The hospital system's table T1 stores records of sets containing patient ID, specimen ID, and vaccine ID. Here, the vaccine ID is stored in table T1, for example, when it is notified by the management system 5.

[0059] Table T2 of the Genetic Analysis System 2 stores records containing pairs of sample IDs and sequence file names. Here, the sequence files are stored, for example, in a predetermined directory. This allows the Genetic Analysis System 2 to retrieve the sequence file by referencing the sequence file name in Table T2.

[0060] Table T3 of the recipe creation system 3 stores records containing pairs of sequence file names, recipe IDs, and recipe file names. For example, sequence files are stored in a predetermined directory. This allows the recipe creation system 3 to retrieve a sequence file by referencing its sequence file name. Similarly, recipe files are stored in a predetermined directory. This allows the recipe creation system 3 to retrieve a recipe file by referencing its recipe file name.

[0061] Table T4 of the vaccine manufacturing facility system 4 stores records containing pairs of recipe file names (name of the recipe file) and vaccine IDs. Here, the recipe files are stored, for example, in a predetermined directory. This allows the vaccine manufacturing facility system 4 to retrieve the recipe file by referencing its name.

[0062] Figure 4 is an example of a sequence diagram according to this embodiment. The processing of the processor in each system is described below, but for readability reasons, the term "processor" will not be explicitly used.

[0063] (Step S10) First, the hospital system 1 assigns a patient ID to identify the target patient and a group of specimen IDs to identify the target specimens of the target patient (for example, normal tissue or blood, and cancerous tissue), and stores them as new records in the hospital system 1's table T1 (see Figure 3). Here, as an example, the first four digits of the specimen ID are assumed not to overlap with other specimen IDs. Furthermore, the hospital system 1 sends, for example, a hospital ID to identify the hospital (or hospital system 1), and this pair of patient ID and specimen ID to the management system 5.

[0064] (Step S20) When the management system 5 receives a set of hospital ID, patient ID, and specimen ID, it assigns a common ID that does not overlap with other common IDs, associates this common ID with the received set of hospital ID, patient ID, and specimen ID, and stores it as a new record in the management system 5's table T5 (see Figure 3).

[0065] (Step S30) Next, the hospital system 1 sends the sample ID group sent in step S10 to the gene analysis laboratory system 2. At the same time, the hospital sends the target sample group (for example, normal tissue or blood, and cancerous tissue) to the gene analysis laboratory. Furthermore, this group of sample IDs may not be transmitted via communication; instead, it may be stored in non-volatile memory (e.g., flash memory) and sent together with the sample.

[0066] (Step S40) When the gene analysis laboratory receives the sample ID group and the sample, it performs gene sequencing on the sample, generates a sequence file containing the gene sequence, and saves it in a predetermined directory for sequence files. Here, as an example, a naming convention is established so that the sequence file name does not overlap with other sequence file names. For example, the sequence file name includes the first four digits of the sample ID. This ensures that the first four digits of the sample ID do not overlap with other sample IDs, thus avoiding duplication of sequence file names. The gene analysis laboratory system 2 stores a new record of this pair of sample ID and sequence file name in table T2. The gene analysis laboratory system 2 also sends this sequence file and the sample ID group to the management system 5.

[0067] (Step S50) When the management system 5 receives a sequence file and a sample ID, it searches for a record in table T5 of the management system 5 using the received sample ID as the key, and updates the sequence file name of this record with the name of the received sequence file. The management system 5 also stores the sequence file in a directory predetermined for sequence files. As a result, since this sample ID is already associated with a common ID, the sequence file is also associated with the common ID.

[0068] (Step S60) The management system 5 sends this sequence file to, for example, the recipe creation agency system 3. The recipe creation agency system 3 receives this sequence file.

[0069] (Step S70) When the recipe creation system 3 receives a sequence file, it predicts a vaccine recipe using the gene sequence stored in the sequence file. Specifically, for example, the recipe creation system 3 predicts a peptide sequence. The recipe creation system 3 stores the predicted vaccine recipe in a recipe file. Here, as an example, a naming convention is established so that the recipe file name does not overlap with other recipe file names.

[0070] (Step S80) The recipe creation system 3 assigns a recipe ID that does not overlap with other recipe IDs, and stores the file name of the sequence file received in step S60, this recipe ID, and the recipe file generated in step S70 as a new record in the table T3 of the recipe creation system. Then the recipe creation system 3 sends this file name of the sequence file, this recipe ID, and this recipe file to the management system 5.

[0071] (Step S90) When the management system 5 receives the information sent in step S80, it extracts a record from table T5 using the sequence file name as the key, and updates the recipe ID and recipe file name of this record with the received recipe ID and the received recipe file name. In this way, the management system 5 stores the recipe ID and recipe file name in association with the sequence file name. The management system 5 also stores the recipe file in a directory predetermined for recipe files.

[0072] (Step S100) The management system 5 sends the received recipe file to the vaccine manufacturing facility system 4.

[0073] (Step S110) When the vaccine manufacturing facility system 4 receives the recipe file, the vaccine manufacturing facility manufactures the vaccine based on the recipe stored in the recipe file. The vaccine manufacturing facility system 4 then assigns a vaccine ID to the manufactured vaccine.

[0074] (Step S120) The vaccine manufacturing facility system 4 sends the combination of the recipe file name of the received recipe file and the vaccine ID issued in step S110 to the management system 5. Alternatively, the recipe file itself may be sent instead of just the recipe file name. Furthermore, the vaccine manufacturing facility system 4 adds a record of this recipe file name and vaccine ID pair to the vaccine manufacturing facility system's table T4 (see Figure 3).

[0075] (Step S130) The management system 5 receives the combination of the recipe file name and the vaccine ID. The management system 5 then searches for a record in the management system table T5 using the received recipe file name as the key, and updates the vaccine ID of the retrieved record with the received vaccine ID. In this way, the management system 5 stores the received vaccine ID in association with the received recipe file name.

[0076] (Step S140) The management system 5 reads the sample ID and hospital ID stored in the same record as the received vaccine ID from the management system table T5, and sends this vaccine ID and the read sample ID (or set of sample IDs) to the hospital system 1, which is identified by the hospital ID. The hospital system 1 receives this pair of vaccine ID and sample ID, searches the hospital system table T1 (see Figure 3) using this sample ID as a key, and updates the vaccine ID of the record obtained from the search with the received vaccine ID.

[0077] <Vaccine Order Screen> Next, we will explain the vaccine ordering screen displayed on the hospital terminal 11 using Figure 5. Figure 5 is an example of the vaccine ordering screen displayed on the hospital terminal 11. As shown in Figure 5, the vaccine ordering screen G1 displays a text box B11 for entering the patient's name, a text box B12 for entering the patient's ID, a text box for entering the specimen ID, a text box for entering the name or ID of the attending physician, a select box B15 for whether or not to provide patient consent, a text box B16 for entering the attending physician's contact information (e.g., email address), a text box B17 for selecting the notification method from the management system 5, a text box B18 for entering whether or not to provide electronic medical record data, and an order button B19.

[0078] If system notification is selected as the notification method, information from management system 5 (e.g., progress information, errors, etc.) will be sent to hospital system 1. On the other hand, if email notification is selected as the notification method, information from management system 5 (e.g., progress information, errors, etc.) will be sent via email to the attending physician's email address. If "Provided" is selected for electronic medical record data provision, the patient's electronic medical record data will be provided to management system 5. On the other hand, if "Not Provided" is selected for electronic medical record data provision, the patient's electronic medical record data will not be provided to management system 5.

[0079] When the order button B19 is pressed, the hospital system 1 sends the entered information to the management system 5 at step S10 in Figure 4. At that time, if "Available" is selected for the provision of electronic medical record data, the electronic medical record data of the patient may be sent to the management system 5.

[0080] The specimen ID may be automatically determined and entered by the hospital system 1.

[0081] <Progress management screen on hospital terminals> Next, the progress management screen displayed on the hospital terminal 11 will be explained using Figure 6. As an example, the management system 5 manages patient ID, status, and progress in a database. Upon request from the hospital terminal 11, the management system 5 sends back information to display the progress management screen, and the progress management screen is displayed on the hospital terminal 11 based on that information.

[0082] Figure 6 shows an example of a progress management screen displayed on a hospital terminal. As shown in Figure 6, the progress management screen G2 displays the patient ID, the status of the target vaccine, the progress of the vaccine's process, the delivery date / delivery confidence level, and the vaccine's administration schedule. Statuses include, for example, "In Production" indicating vaccine preparation, "Error" indicating errors in the process, and "Completed" indicating vaccine administration. Here, "In Production" is displayed in bold as an example of visual highlighting. This allows healthcare personnel using the hospital terminal to understand that the vaccine is being prepared. Visual highlighting here includes, for example, decoration of the text itself such as a different color or thickness of the text, decoration of the background of the text such as a different background color or pattern, decoration around the text such as an underline or emphasis dots, or a combination thereof. Note that the status is not limited to visual highlighting; for example, the status may display one of the following: "In Production" indicating vaccine preparation, "Error" indicating errors in the process, or "Completed" indicating vaccine administration.

[0083] The progress of the vaccine production process is indicated, showing which stage it is currently in. Progress can include, for example, sample transport, sequencing, sequencing complete, PCV prediction, PCV prediction complete, vaccine manufacturing, vaccine manufacturing complete, vaccine transport, arrived at hospital, administered to patient, and manufacturing interrupted. Here, "PCV prediction" is shown in bold as an example of visual highlighting. This allows healthcare professionals using hospital terminals to understand that the vaccine recipe is being predicted. Visual highlighting, as mentioned above, can include, for example, different font color or thickness, background color or pattern, underlining or dots around the text, or a combination thereof. Note that progress is not limited to visual highlighting; for example, any one of the above may be displayed.

[0084] The progress management screen G2 also displays a text box B21 and a send button B22 for doctors to update the progress. When the send button B22 is pressed, the information entered in text box B21 is sent to the management system 5, and the database in the management system 5 is updated.

[0085] On the progress management screen G2, an image showing the progress status is displayed in the center as an example. Here, it is shown that the PCV forecasting vendor is in the process of creating the vaccine recipe. The progress management screen G2 also displays the remaining time until vaccine delivery. This remaining time until vaccine delivery is determined by management system 5. The following describes a specific example of how the predicted delivery date or predicted time required for vaccine delivery (including the remaining time until vaccine delivery mentioned above) is determined.

[0086] <Method 1 for determining the predicted delivery date or estimated required time: When using a pre-set value> First, at gene analysis institutions (e.g., sequencing vendors), recipe creation institutions (e.g., vaccine recipe prediction system vendors), and vaccine manufacturing institutions (e.g., vaccine manufacturing system vendors), the time it takes for each system to receive data and samples from the upstream process and deliver the deliverables to the downstream process is collected (by interviewing vendors in advance to find out how long it will take). Furthermore, the time incurred when moving between processes is collected (collected from transportation companies, etc.), and the management system 5 determines the predicted delivery date. At this time, the estimated time required for the entire process and each process is calculated and stored in the storage 53 of the management system 5. The management system 5 may also determine the remaining time until vaccine delivery by summing the estimated time required for the remaining processes until vaccine delivery and the estimated time required when moving between the remaining processes.

[0087] Management system 5 detects delays if the actual time taken for a particular process exceeds the estimated time stored for each process, and notifies the hospital system 1 or the attending physician. Methods of notifying the attending physician include, for example, sending a notification to the attending physician's email address, notifying via API integration with an external application, or notifying via the system screen.

[0088] <Method 2 for determining the predicted delivery date or estimated required time: When using pre-set values> First, the time it takes for each system to receive data and / or samples from the upstream process and transfer the deliverables to the downstream process is collected from the gene analysis institution (e.g., sequencing vendor), recipe creation institution (e.g., vaccine recipe prediction system vendor), and vaccine manufacturing institution (e.g., vaccine manufacturing system vendor). In this case, it is preferable that the system automatically collects the time taken at each process, and it is preferable that the management system 5 acquires these collected times from each system.

[0089] Furthermore, the management system 5 calculates the time that occurs when moving between processes. For example, the management system 5 may calculate this by subtracting the time taken for each of the two consecutive processes from the total actual time taken for those two processes. The management system 5 may also calculate the average or median of the actual time taken for each collected process as the predicted time taken and store it in the storage 53 of the management system 5. Alternatively, the management system 5 may use the total actual time taken for each process to determine the average or median of the total time taken as the predicted delivery date and store this predicted delivery date in the storage 53 of the management system 5.

[0090] The management system 5 may also determine the remaining time until vaccine delivery by summing the average or median actual time required for the remaining processes until vaccine delivery and the average or median actual time required when crossing between the remaining processes.

[0091] Furthermore, if sufficient actual delivery times have been collected, the management system 5 may determine the estimated delivery date by inputting at least one of the following into the trained machine learning model: the number of gene fragments and / or the base amount of the gene to be read, the amount of sequence data, or the number of gene mutations. Here, the machine learning model is trained using training data that takes at least one of the following as input: the number of gene fragments and / or the base amount of the gene to be read, the amount of sequence data, or the number of gene mutations, and outputs the estimated delivery date.

[0092] The management system 5 may detect delays if the actual time taken for a particular process exceeds the estimated time stored for each process, and may notify the hospital system 1 or the attending physician. Methods of notifying the attending physician include, for example, sending a notification to the attending physician's email address, notifying via API integration with an external application, or notifying via the system screen.

[0093] <Variations of methods for determining the predicted delivery date or estimated required time> The delivery time management means 561 determines an estimated time for analyzing the gene according to the number of gene fragments (reads) obtained from the sample and / or the base amount of the gene to be read. Alternatively, the delivery date management means 561 may determine the estimated time to create the recipe according to the amount of sequence data obtained as a result of the gene analysis (for example, the size of the sequence file). Alternatively, the delivery date management means 561 may determine the estimated time required to create the recipe according to the number of gene mutations. Alternatively, the delivery date management means 561 may determine the estimated time to prepare the recipe according to the name of the organ from which the sample was obtained.

[0094] Since there are ambiguities regarding the determination of the delivery date, management system 5 may also notify the degree of confidence in the delivery date. For example, there are two methods for calculating the degree of confidence:

[0095] <Example 1 of a method for calculating delivery date confidence: A method that increases confidence with each completion of a process> Management system 5 increases the confidence level of delivery dates when processes such as the sequencing process, vaccine recipe prediction process, and vaccine manufacturing process transition (for example, increasing it from 20% to 40% when the sequencing process is completed).

[0096] <Second example of a method for calculating delivery date confidence: A method to increase confidence compared to actual values> The management system 5 collects the actual required time for each process, determines the average or median value as a threshold for each process, and lowers the confidence level if each process falls below the corresponding threshold, and raises the confidence level if it exceeds it. Alternatively, the management system 5 may learn from the actual required time for each process using machine learning or other methods, and use the resulting prediction as the confidence level.

[0097] <Regarding patient administration schedules> The management system 5 may allow terminal 1 to set the patient administration date if the confidence level exceeds a set value (e.g., 80%). For example, if the confidence level exceeds a set value (e.g., 80%), the management system 5 may change the progress management screen G2 so that the hospital can determine the scheduled administration date for the patient from the calendar, or it may change the progress management screen G2 so that multiple candidates can be specified.

[0098] <Example of a progress management screen for the analyst terminal, creator terminal, or manufacturer terminal> Figure 7 shows an example of a progress management screen displayed on an analyst terminal, creator terminal, or manufacturer terminal. As shown in Figure 7, progress management screen G3 displays the patient ID, the status of the target vaccine, and the progress of the vaccine's process. Here, the status can be, for example, "In Production" indicating vaccine preparation, "Error" indicating an error in the process, or "Completed" indicating vaccine administration. Here, as an example, "In Production," which is an example of the current status, is displayed in bold as an example of visual highlighting. This allows healthcare personnel using hospital terminals to understand that the vaccine is being prepared. Visual highlighting, as mentioned above, can include, for example, different font color or font weight, decoration of the text's background, such as different background color or pattern, or decoration around the text, such as underlining or emphasis dots, or a combination thereof. Note that the status is not limited to visual highlighting; for example, the status may display one of the following: "In Production" indicating vaccine preparation, "Error" indicating an error in the process, or "Completed" indicating vaccine administration.

[0099] The progress of the vaccine production process is indicated, showing which stage it is currently in. Progress can include, for example, sample transport, sequencing, sequencing complete, PCV prediction, PCV prediction complete, vaccine manufacturing, vaccine manufacturing complete, vaccine transport, arrived at hospital, administered to patient, and manufacturing interrupted. Here, "PCV prediction" is shown in bold as an example of visual highlighting. This allows healthcare professionals using hospital terminals to understand that the vaccine recipe is being predicted. Visual highlighting, as mentioned above, can include, for example, different font color or font weight, background color or pattern, or surrounding text decoration such as underlining or emphasis marks, or a combination thereof. Note that progress is not limited to visual highlighting; for example, any one of the above may be displayed.

[0100] The progress management screen G3 also displays a text box B31 and a send button B32 for each user to update their progress. When the send button B32 is pressed, the information entered in text box B31 is sent to the management system 5, and the database in the management system 5 is updated.

[0101] On progress management screen G3, an image showing the progress status is displayed in the center as an example. Here, it is shown that the PCV prediction vendor is in the process of creating the vaccine recipe. Progress management screen G3 also displays the remaining time until vaccine delivery. As mentioned above, this remaining time until vaccine delivery is determined by management system 5.

[0102] <Data subject to access control> Next, we will explain the data subject to access control. This data includes, for example, the following: (1) Common ID (2) Sequencing data (DNA and RNA information collected from patient samples. For PCV prediction, this includes three types: cancer DNA, normal DNA, and cancer RNA.) (3) Clinical data (data registered in the hospital's electronic medical record system. Data will be collected only to the extent that consent has been obtained from the hospital and the patient. For example, medical history, pre-examination results, questionnaires, etc.)

[0103] (4) Sequence report (data issued by a gene analysis laboratory that relates to the quality of genome sequencing, such as the average DNA read length and RIN value) (5) QC (Quality Control) data and intermediate analysis data (intermediate data or data related to the quality of prediction or genome analysis when the recipe creation system or gene analysis system processes genome data, including data from which QC has been performed on the genome data and its intermediate data as preprocessing, and / or data from which QC has been performed on the PCV recipe itself. For example, the average read length of DNA, presence or absence of contamination, confidence level of HLA typing, number of candidates included in the PCV recipe, etc.) (6) Vaccine manufacturing quality data (data related to quality when vaccine manufacturers produce vaccines based on digital vaccine recipes. For example, temperature during vaccine production, peptide purity, and pass / fail criteria for shipment.)

[0104] (7) Laboratory data (This refers to experimental data from laboratories used to validate vaccine recipes, and experimental data from laboratories used to validate the addition of candidate epitopes to vaccine recipes. For example, measured binding values ​​of epitopes, immunogenicity values, etc.) (8) Post-administration monitoring data (data showing the patient's health status after vaccine administration, such as recurrence biomarkers and cancer screening test items) (9) System logs (The raw logs can only be viewed by administrators operating this system, for example, and serve as the source information for notifications in the event of errors or updates to the progress of the vaccine manufacturing process.)

[0105] <Lab integration> Furthermore, laboratory experiments may be incorporated into the process, either in addition to or as a substitute for recipe development institutions. Laboratory data can also be used for (1) accuracy verification of the recipe development institution system, or (2) as a supplement to vaccine recipes based on actual experiments.

[0106] <List of access restrictions> Next, we will explain an example of access permissions for each organization for the nine types of data mentioned above, using Figure 8. Figure 8 is an example of a list of access restrictions for the data. The table in Figure 8 shows the access permissions for the nine types of data mentioned above for each organization: hospitals, genetic analysis laboratories, recipe development laboratories, vaccine manufacturing laboratories, the administrator of management system 5, and lab vendors. In the table in Figure 8, ○ indicates access is permitted, and × indicates access is denied. The access restrictions in this table may be stored as a table in the storage 53 of management system 5, and access restrictions may be imposed based on this table.

[0107] <Search results screen on hospital terminals> Next, an example of a search results screen on the hospital terminal 11 will be explained using Figure 9. Figure 9 is an example of a search results screen displayed on the hospital terminal. In the search results screen G4 of Figure 9, a text box B41 for entering a patient ID and a search button B42 are shown. The search results screen G4 of Figure 9 is an example of the screen displayed after a patient ID has been entered into text box B41 and the search button B42 has been pressed.

[0108] For each patient ID being searched, the following information is displayed: vaccine status, progress, URL for viewing sequence reports, URL for viewing QC data, URL for viewing vaccine manufacturing quality data, URL for viewing laboratory data, URL for viewing clinical data (pre-administration), and URL for viewing monitoring data. Some data cannot be viewed due to insufficient permissions, and a message indicating that the data cannot be disclosed is displayed as an example.

[0109] The management system 5 according to this embodiment includes a delivery date management means that determines a predicted delivery date or predicted time required for the administration to be delivered to the hospital, using the estimated time or actual time required for the analysis institution to analyze the genes of the patient's sample, the estimated time or actual time required for the preparation institution to create a recipe for the administration to the patient from the gene analysis results, and the estimated time or actual time required for the manufacturing institution to manufacture the administration from the recipe, and a communication control means that transmits information for displaying the predicted delivery date or predicted time required to a terminal.

[0110] In other words, the management method according to this embodiment includes a determination step in which the management system determines a predicted delivery date or predicted time required for the administration to be delivered to the hospital, using the estimated time or actual time required for the analysis institution to analyze the genes of the patient's sample, the estimated time or actual time required for the preparation institution to create a recipe for the administration to the patient from the gene analysis results, and / or the estimated time or actual time required for the manufacturing institution to manufacture the administration from the recipe; and a transmission step in which information for displaying the predicted delivery date or predicted time required is transmitted to a terminal.

[0111] The management method according to this embodiment further includes a step in which, when a request for the progress status of a drug (e.g., vaccine) is received from a terminal (e.g., hospital terminal 11, analyst terminal 21, creator terminal 31, or manufacturer terminal 41), the management system sends back information to the terminal for displaying the progress status. The terminal then uses the returned information to display the progress status.

[0112] The management method according to this embodiment further includes a step in which viewing privileges are assigned to each institution and stored in a storage device, and in the step of replying, the progress status is replied to the extent permitted by the viewing privileges assigned to the institution to which the terminal that requested the progress status belongs.

[0113] The management method according to this embodiment further includes the step of notifying the patient's attending physician via a physician terminal logged into the service provided by the management system, or the attending physician of the patient, if the delivery is delayed beyond the predicted delivery date or the predicted required time.

[0114] The management method according to this embodiment further includes a step of enabling the setting of an administration schedule for the patient if the confidence level of the delivery date exceeds a certain standard.

[0115] The management method according to this embodiment further includes the steps of: when gene sequencing data is received from the analysis institution, the management system 5 transmits the gene sequencing data to the recipe creation institution system 3; and when a recipe is received from the creation institution, the management system 5 transmits the recipe to the vaccine manufacturing institution system 4.

[0116] The management method according to this embodiment further includes the step of writing the update history and / or update data of the storage 53 to the blockchain.

[0117] There may be multiple candidates for the analysis institution and / or the preparation institution and / or the manufacturing institution, in which case the delivery date management means 561 may, in the decision step, determine the predicted delivery date or predicted time required for the administration body to be delivered to the hospital, depending on the analysis institution and / or the preparation institution and / or the manufacturing institution of the ordering party.

[0118] <Example 1> Next, we will explain Modification 1 of the data management method. In Modification 1, when the management system 5 receives a specimen ID from the hospital system 1, it issues a common ID, and the hospital and each institution manage the data using the common ID.

[0119] Figure 10 shows the schematic configuration of the databases for each system in Modification 1. As shown in Figure 10, the management system table T5b stores records of pairs of names: a hospital ID to identify the hospital, a patient ID to identify the patient, a specimen ID to identify the specimen, a common ID for managing the data, a sequence file name which is the name of the sequence file containing the gene sequence sequenced from the patient's specimen, and a recipe file name which is the name of the recipe file containing the vaccine recipe. Here, similarly in Modification 1, the sequence files are stored, for example, in a predetermined directory for sequence files.

[0120] Similarly in Modification 1, sample IDs are assigned to both the patient's normal tissue or blood and the patient's cancerous tissue. Here, as an example, the only difference between the sample ID assigned to the patient's normal tissue or blood and the sample ID assigned to the patient's cancerous tissue is the last digit.

[0121] Similarly, in Modification 1, the sequence files include a file containing the sequence of normal tissue DNA (also called normal DNA), a file containing the sequence of cancerous tissue DNA (also called cancer DNA), and a file containing the sequence of cancerous tissue RNA (also called cancer RNA). The file names of each sequence are stored in table T5b, and each sequence file is stored in storage 53.

[0122] In Modification 1, the hospital system's table T1b differs from the hospital system's table T1 in Figure 3 in that it stores a common ID instead of a vaccine ID. Here, the common ID is stored in table T1b by the hospital system 1 when it is notified, for example, from the management system 5.

[0123] Table T2b of the gene analysis system in Modification 1 differs from Table T2 of the gene analysis system in Figure 3 in that it also stores a common ID. Here, the common ID is stored in Table T2b by the gene analysis system when it is notified by, for example, the management system 5.

[0124] In Modification Example 1, table T3b of the recipe creation system 3 differs from table T3 of the recipe creation system 3 in Figure 3 in that it stores a common ID instead of a recipe ID. Here, the common ID is stored in table T3b by the recipe creation system 3 when it is notified by the management system 5, for example.

[0125] In Modification 1, table T4b of the vaccine manufacturing facility system 4 differs from table T4 of the vaccine manufacturing facility system 4 in that it stores a common ID instead of a vaccine ID. Here, the common ID is stored in table T4b by the vaccine manufacturing facility system 4 when it is notified by the management system 5, for example.

[0126] Figure 11 is an example of a sequence diagram relating to Modification 1. The processing of the processor in each system is described below, but for readability reasons, the term "processor" will not be explicitly used.

[0127] (Step S210) First, the hospital system 1 assigns a patient ID to identify the target patient and a set of sample IDs to identify the sample group of the target patient (for example, normal tissue or blood, and cancerous tissue), and stores them as new records in the hospital system 1's table T1b (see Figure 10). Here, as an example, it is assumed that the first four digits of the sample ID do not overlap with other sample IDs. Furthermore, the hospital system 1 sends, for example, a hospital ID to identify the hospital (or hospital system 1), and this set of patient ID and sample ID to the management system 5.

[0128] (Step S220) When the management system 5 receives a set of hospital ID, patient ID, and specimen ID group, it assigns a common ID that does not overlap with other common IDs, associates this common ID with the received set of hospital ID, patient ID, and specimen ID, and stores it as a new record in the management system 5's table T5b (see Figure 10).

[0129] (Step S230) Next, the management system 5 notifies the hospital system 1 of the common ID that it has issued. When the hospital system 1 receives this common ID, it updates the common ID of the record in table 1b that contains the patient ID and specimen ID group sent in step S210 with this received common ID.

[0130] (Step S240) Compared to step S30 in Figure 4, the difference is that hospital system 1 sends the common ID received in step S230 to gene analysis laboratory system 2, in addition to the sample ID group sent in step S210. At the same time, the hospital sends the samples identified by the sample ID (for example, normal tissue or blood, and cancerous tissue) to the gene analysis laboratory. Furthermore, this sample ID and common ID may not be transmitted via communication; instead, they may be stored in non-volatile memory (e.g., flash memory) and sent together with the sample.

[0131] (Step S250) When the gene analysis laboratory receives the sample ID, common ID, and sample, it performs gene sequencing on the sample and generates a sequence file containing the gene sequence. Here, as an example, a naming convention is established so that the sequence file name does not overlap with other sequence file names. For example, the sequence file name includes the first four digits of the sample ID. This ensures that the first four digits of the sample ID do not overlap with other sample IDs, thus avoiding duplication of sequence file names.

[0132] Compared to step S40 in Figure 4, the gene analysis system 2 differs in that it stores a new record in table T2b that includes the common ID in addition to the sequence file name of the sample ID. Also, compared to step S40 in Figure 4, the gene analysis system 2 differs in that it sends the common ID, rather than the sample ID, to the management system 5 in addition to the sequence file.

[0133] (Step S260) When the management system 5 receives a sequence file and a common ID, it searches for a record in table T5b of the management system 5 using the received common ID as the key, and updates the sequence file name of this record with the name of the received sequence file. The management system 5 also stores the sequence file in a directory predetermined for sequence files.

[0134] (Step S270) In comparison with step S60 in Figure 4, the management system 5 differs in that, for example, it sends the received common ID in addition to the generated sequence file to the recipe creation agency system 3. The recipe creation agency system 3 receives this sequence file and common ID.

[0135] (Step S280) When the recipe creation system 3 receives a sequence file and a common ID, it predicts a vaccine recipe using the gene sequence stored in the sequence file. Specifically, for example, the recipe creation system 3 predicts a peptide sequence. The recipe creation system 3 stores the predicted vaccine recipe in a recipe file. Here, as an example, a naming convention is established so that the recipe file name does not overlap with other recipe file names.

[0136] (Step S290) In comparison with step S80 in Figure 3, the recipe creation system 3 differs in that it stores the filename of the sequence file received in step S270 and the recipe file generated in step S280 as a pair with the common ID received in step S270, rather than the recipe ID, as a new record in the table T3b of the recipe creation system. Here, as an example, a naming convention is established so that the recipe file name does not overlap with other recipe file names. In comparison with step S80 in Figure 3, the difference is that the recipe creation system 3 sends a common ID to the management system 5 in addition to the recipe file generated in step S280, instead of the recipe ID and sequence file name.

[0137] (Step S300) When the management system 5 receives the information sent in step S290, it extracts a record from table T5b using the common ID as the key and updates the recipe file name of this record with the received recipe file name. In this way, the management system 5 stores the recipe file associated with the common ID. The management system 5 also stores the recipe file in a directory predetermined for recipe files.

[0138] (Step S310) Compared to step S100 in Figure 3, the management system 5 differs in that, in addition to the received recipe file, it also sends a common ID to the vaccine manufacturing system 4. When the vaccine manufacturing system 4 receives the recipe file and the common ID, the vaccine manufacturing system manufactures the vaccine based on the recipe stored in the recipe file.

[0139] (Step S320) The vaccine manufacturing facility system 4 transmits the common ID and a message indicating that vaccine manufacturing is complete to the management system 5.

[0140] (Step S330) When the management system 5 receives the common ID and the notification that vaccine manufacturing is complete, it notifies the hospital system 1 of this common ID and the notification that vaccine manufacturing is complete.

[0141] <Modification 2> Next, we will explain Modification 2 of the data management method. In Modification 2, when the management system 5 receives the hospital ID, sample ID group, and sequence file from the gene analysis laboratory system 2, it issues a common ID, associates this common ID with the received sample ID group, stores it, keeps the patient ID within the hospital system 1 and does not transmit it externally, the gene analysis laboratory system 2 manages the data using the sample ID, the recipe creation laboratory system 3 manages the data using the recipe ID, and the vaccine manufacturing laboratory system 4 manages the data using the vaccine ID.

[0142] Figure 10 shows the schematic configuration of the databases for each system in Modification 2. Table T5c of the management system has the patient ID column removed from the records, compared to Table T5 of the management system in Figure 3. Here, as in Figure 3, sequence files are stored in a predetermined directory, for example. Similarly, recipe files are stored in a predetermined directory, for example.

[0143] Similar to Figure 3, the sequence files include files containing sequences of normal tissue DNA (also called normal DNA), files containing sequences of cancerous tissue DNA (also called cancer DNA), and files containing sequences of cancerous tissue RNA (also called cancer RNA). The file names of each sequence are stored in table T5c, and each sequence file is stored in storage 53.

[0144] The hospital system table T1c, like the hospital system table T1 in Figure 3, stores records of sets of patient ID, specimen ID, and vaccine ID. Here, the vaccine ID is stored in table T1, for example, when it is notified by the management system 5.

[0145] Table T2c of Genetic Analysis System 2 has an added hospital ID column compared to Table T2 of Genetic Analysis System 2 in Figure 3. Similar to Figure 3, sequence files are stored, for example, in a predetermined directory for sequence files.

[0146] Table T3c of the Recipe Creation System 3 stores records of sequences, recipe IDs, and recipe file names, similar to Table T3 of the Recipe Creation System 3 in Figure 3. Here, as in Figure 3, sequence files are stored in a predetermined directory for sequence files, and recipe files are stored in a predetermined directory for recipe files, for example.

[0147] Table T4c of the vaccine manufacturing facility system 4 stores records of pairs of recipe file names (name of the recipe file) and vaccine IDs, similar to Table T4 of the vaccine manufacturing facility system 4 in Figure 3. Here, as in Figure 3, the recipe files are stored, for example, in a predetermined directory for recipe files.

[0148] Figure 13 is an example of a sequence diagram relating to Modification 2. The following describes the processing of the processor in each system, but for readability reasons, the term "processor" will not be explicitly used.

[0149] (Step S410) First, the hospital system 1 transmits the hospital ID and the sample IDs assigned to the target sample group to the gene analysis laboratory system 2. At the same time, the hospital sends the target samples (for example, normal tissue or blood, and cancerous tissue) to the gene analysis laboratory. Furthermore, this hospital ID and specimen ID group may not be transmitted via communication; instead, the specimen ID may be stored in non-volatile memory (e.g., flash memory) and sent together with the specimen.

[0150] (Step S420) When the gene analysis laboratory receives the hospital ID, sample ID, and sample, it performs gene sequencing on the sample, generates a sequence file containing the gene sequence, and saves it in a predetermined directory for sequence files. Here, as an example, a naming convention is established so that the sequence file name does not overlap with other sequence file names. For example, the sequence file name includes the first four digits of the sample ID. This prevents duplication of sequence file names because the first four digits of the sample ID do not overlap with other sample IDs. The gene analysis laboratory system 2 stores a new record of this hospital ID, sample ID, and sequence file name set in table T2c. Furthermore, the gene analysis system 2 transmits the hospital ID in addition to the sequence file and sample ID group to the management system 5.

[0151] (Step S430) When the management system 5 receives this sequence file, sample ID group, and hospital ID, it assigns a common ID.

[0152] (Step S440) The management system 5 then adds a new record containing the received sample IDs, the filenames of the received sequence files, and the assigned common ID to table T5c of the management system 5. In this way, the management system 5 stores the received sample IDs and the filenames of the received sequence files in association with the assigned common ID. The management system 5 also stores the sequence files in a directory predetermined for sequence files.

[0153] (Step S450) Similar to step S60 in Figure 4, the management system 5 sends this sequence file to, for example, the recipe creation agency system 3. The recipe creation agency system 3 receives this sequence file.

[0154] (Step S460) Similar to step S70 in Figure 4, when the recipe creation system 3 receives a sequence file, it predicts a vaccine recipe using the gene sequence stored in the sequence file. Specifically, for example, the recipe creation system 3 predicts a peptide sequence. The recipe creation system 3 stores the predicted vaccine recipe in a recipe file. Here, as an example, a naming convention is established so that the recipe file name does not overlap with other recipe file names.

[0155] (Step S470) Similar to step S80 in Figure 4, the recipe creation system 3 assigns a recipe ID that does not overlap with other recipe IDs, and stores the sequence file name received in step S450, this recipe ID, and the recipe file generated in step S460 as a new record in the recipe creation system's table T3. Then, the recipe creation system 3 sends this sequence file name, this recipe ID, and this recipe file to the management system 5.

[0156] (Step S480) Similar to step S90 in Figure 4, when the management system 5 receives the information transmitted in step S470, it extracts a record in table T5c using the received sequence file name as the key, and updates the recipe ID and recipe file name of this record with the received recipe ID and the file name of the received recipe file. In this way, the management system 5 stores the recipe ID and recipe file name in association with the sequence file name. The management system 5 also stores the recipe file in a directory predetermined for recipe files.

[0157] (Step S490) Similar to step S100 in Figure 4, the management system 5 sends the received recipe file to the vaccine manufacturing facility system 4.

[0158] (Step S500) If the vaccine manufacturing facility system 4 receives the recipe file, similar to step S110 in Figure 4, the vaccine manufacturing facility manufactures the vaccine based on the recipe stored in the recipe file. The vaccine manufacturing facility system 4 then assigns a vaccine ID to the manufactured vaccine.

[0159] (Step S510) Similar to step S120 in Figure 4, the vaccine manufacturing facility system 4 sends the combination of the recipe file name of the received recipe file and the vaccine ID issued in step S500 to the management system 5. Alternatively, the recipe file itself may be sent instead of just the recipe file name. The vaccine manufacturing facility system 4 also adds a record of this combination of recipe file name and vaccine ID to the vaccine manufacturing facility system's table T4c (see Figure 12).

[0160] (Step S520) Similar to step S130 in Figure 4, the management system 5 receives this recipe file name and this vaccine ID pair. The management system 5 then searches the record in the management system table T5c using the received recipe file name as the key, and updates the vaccine ID of the retrieved record with the received vaccine ID. In this way, the management system 5 stores the received vaccine ID in association with the received recipe file name.

[0161] (Step S530) Similar to step S140 in Figure 4, the management system 5 reads the sample ID and hospital ID stored in the same record as the received vaccine ID from the management system's table T5c, and sends this vaccine ID and the read sample ID (or set of sample IDs) to the hospital system 1, which is identified by the hospital ID. The hospital system 1 receives this pair of vaccine ID and sample ID, searches the hospital system's table T1c using this sample ID as a key, and updates the vaccine ID in the record obtained from the search with the received vaccine ID.

[0162] Furthermore, as shown in Figure 14, the electronic medical record system 6 may also include a management system 5. Figure 14 is a schematic block diagram of an information processing system according to a modified example of this embodiment. As shown in the information processing system Sb of Figure 14, the management system 5 may be incorporated into a part of the electronic medical record system 6.

[0163] Furthermore, at least a part of the management system 5 described in the above-mentioned embodiment may be configured as hardware or as software. In the case of software configuration, a program that implements at least a part of the functions of the management system 5 may be stored on a computer-readable recording medium and loaded and executed by a computer. The recording medium is not limited to removable ones such as magnetic disks or optical disks, but may also be a fixed recording medium such as a hard disk drive or memory.

[0164] Furthermore, a program that implements at least some of the functions of management system 5 may be distributed via communication lines such as the Internet (including wireless communication). In addition, the program may be encrypted, modulated, or compressed and distributed via wired or wireless lines such as the Internet, or stored on a recording medium.

[0165] Furthermore, the management system 5 may be made to function using one or more information devices. If multiple information devices are used, one of them may be a computer, and the computer may execute a predetermined program to realize the function of at least one means of the management system 5.

[0166] Furthermore, in the invention of a method, all steps may be automatically controlled by a computer. Alternatively, each step may be performed by a computer while the progress between steps is controlled manually. Furthermore, at least a portion of all steps may be performed manually.

[0167] As described above, the present invention is not limited to the embodiments described above, and the components can be modified and implemented in practice without departing from the spirit of the invention. Furthermore, various inventions can be formed by appropriately combining the multiple components disclosed in the above embodiments. For example, some components may be deleted from all the components shown in the embodiments. Moreover, components from different embodiments may be appropriately combined. [Explanation of symbols]

[0168] 1. Hospital System 2. Gene Analysis Laboratory System 3. Recipe Creation Agency System 4. Vaccine Manufacturing Facility System 5 Management Systems 6. Electronic Medical Record System 51 Input Interfaces 52 Communication Module 53 Storage 54 memory 55 Output Interfaces 56 processors 561 Delivery date management methods 562 Communication control means 563 ID management means 564 Pipeline Management Methods 565 Genome Information Management Methods 566 Quality information management means S, Sb Information Processing System

Claims

1. A management method performed by a management system to manage the drugs administered to a patient, A decision step in which the management system determines the predicted delivery date or estimated time required for the drug to be delivered to the hospital, using the estimated or actual time required for the analysis institution to analyze the genes of the patient's sample, the estimated or actual time required for the preparation institution to create a recipe for the drug to be administered to the patient from the gene analysis results, and the estimated or actual time required for the manufacturing institution to manufacture the drug from the recipe. A transmission step of sending information to a terminal to display the predicted delivery date or predicted required time, It has, The aforementioned decision step determines the predicted delivery date or the predicted required time by inputting the number of gene fragments and / or the base amount of genes to be read, the amount of sequence data, the number of gene mutations, and the predicted delivery date of the administered substance into a machine learning model that has been trained using the number of gene fragments and / or the base amount of genes to be read, the amount of sequence data, and the number of gene mutations as training data. Management method.

2. There are multiple candidates for the aforementioned analysis facility and / or the aforementioned preparation facility and / or the aforementioned manufacturing facility. In the aforementioned decision step, the estimated delivery date or estimated time required for the administration of the drug to be delivered to the hospital is determined, depending on the ordering party's analysis laboratory and / or the ordering party's preparation laboratory and / or the ordering party's manufacturing laboratory. The management method described in claim 1.

3. When the management system receives a request from the terminal for information regarding the progress of the administered substance, it includes a step in which the management system returns information to the terminal to display the progress status. The control method according to claim 1 or 2.

4. Each institution is assigned access permissions, which are stored in memory. The aforementioned reply step includes a step to reply with the progress to the extent permitted by the viewing permissions assigned to the institution to which the terminal requesting the progress belongs. The management method described in claim 3.

5. If the projected delivery date or estimated time is delayed, the system includes a step to notify the patient's attending physician via a physician's terminal logged into the service provided by the management system, or to the patient's attending physician. The management method described in claim 1.

6. If the confidence level of delivery exceeds a certain standard, the system includes a step to allow the setting of an administration schedule for the patient to be accepted. The management method described in claim 1.

7. When gene sequencing data is received from the aforementioned analysis institution, the management system transmits the gene sequencing data to the system of the aforementioned creation institution. When the management system receives a recipe from the aforementioned creation organization, it transmits the recipe to the manufacturing organization's system. The management method according to claim 1, having the following characteristics.

8. When the management system receives quality information regarding specimens, quality information regarding gene sequencing, quality information regarding recipes, and / or quality information regarding vaccines from a hospital system, analysis laboratory system, preparation laboratory system, and / or manufacturing laboratory system, the management system has a step of storing the received information in a storage device. The management method described in claim 1.

9. The administered substance is a vaccine, and the recipe consists of peptide sequence data of the neoantigen, protein data, and aggregate data of the administered compound. The management method described in claim 8.

10. The step includes writing the update history and / or update data of the aforementioned storage device to the blockchain. The management method described in claim 8.

11. A step to determine the estimated time for analyzing the gene, depending on the number of gene fragments obtained from the sample and / or the base amount of the gene to be read. The management method according to claim 1, having the following characteristics.

12. The step of determining the estimated time required to create the recipe, based on the amount of sequence data obtained from the gene analysis. The management method according to claim 1, having the following characteristics.

13. The step of determining the estimated time required to create the recipe, depending on the number of gene mutations. The management method according to claim 1, having the following characteristics.

14. The step of determining the estimated time required to prepare the recipe, according to the name of the organ from which the sample was obtained. The management method according to claim 1, having the following characteristics.

15. Access control steps that restrict the information that can be accessed by each institution. The management method according to claim 1, further comprising:

16. A delivery date management means for determining the predicted delivery date or predicted time required for the drug to be delivered to the hospital, using the estimated time or actual time required for the analysis institution to analyze the genes of the patient's sample, the estimated time or actual time required for the preparation institution to create a recipe for the drug to be administered to the patient from the gene analysis results, and the estimated time or actual time required for the manufacturing institution to manufacture the drug from the recipe. A communication control means that transmits information to a terminal for displaying the predicted delivery date or predicted required time, Equipped with, The delivery date management means determines the predicted delivery date or the predicted required time by inputting at least one of the following into a machine learning model, which has been trained using the number of gene fragments and / or the base amount of the gene to be read, the amount of sequence data, and the number of gene mutations, along with the predicted delivery date of the administered substance, as training data. Management system.

17. An electronic medical record system comprising the management system described in claim 16.

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